Similarly to traditional non-rigid reconstruction methods that explains non-rigid scenes with a static canonical space and a per-frame deformation model [1]}, Nerfies [2]} capture a non-rigid scene with one canonical NeRF \(F\)  and a per-time step view-to-canonical deformation \(W_{t\rightarrow c}\)  that takes a point \(\mathbf {x}\)  with a time-conditioned latent vector \(\mathbf {\varphi }_t\)  to a canonical point \(\mathbf {x}_c\) ,
\(W_{t\rightarrow c}: (\mathbf {x}, \mathbf {\varphi }_t)\mapsto \mathbf {x}_c.\) 
